Convert between tbl_now and EpiNow2 — tbl_now

EpiNow2 takes several different input shapes, one per entry point, so tbl_now_to_EpiNow2() is told which one you want with target – named after the EpiNow2 function the result is passed to, so it can be handed over unchanged:

"estimate_infections": a data.frame of date / confirm, the series as known at get_now(). Also what EpiNow2::epinow() takes.
"regional_epinow": the same, plus a region column built from the object's strata.
"estimate_truncation": a tbl_now_epinow2_snapshots list – one date/confirm snapshot per report date, which is the one EpiNow2 model that uses the report dimension a tbl_now exists to carry.
"estimate_secondary": a data.frame of date / primary / secondary, where primary counts reported arrivals by report_date and secondary counts resolved revisions by revision_date, filtered by secondary_type. This is a repurposing of EpiNow2::estimate_secondary(): the model was written for two epidemiological streams linked by a delay (cases and deaths, say), and here the two streams are one series and its own revisions, so the fitted delay is report-to-revision. The converter warns about the repurposing when it runs.
"estimate_dist": the interval-censored pdate_lwr / pdate_upr / sdate_lwr / sdate_upr / obs_date frame that EpiNow2::estimate_dist() fits a delay distribution to (new in EpiNow2 1.9.0). Count data rides along as the n weight column. estimate_dist() vendors likelihood functions from primarycensored, and its help asks that you cite primarycensored alongside EpiNow2 when using it (citation("primarycensored")). Like tbl_now_to_epidist(), this target returns one row per observed delay: the revision axis is dropped and undeclared columns are pooled, because neither reaches estimate_dist() and so neither can keep two rows apart.

tbl_now_from_EpiNow2() inverts the snapshot form: snapshot k is the series as known at report date k, so differencing consecutive snapshots recovers count-incidence exactly. There is deliberately no inverse for the other targets: a single series has no report dimension to recover, a secondary stream is already aggregated, and a delay distribution is not case data.

Usage

tbl_now_to_EpiNow2(
  x,
  ...,
  target = c("estimate_infections", "regional_epinow", "estimate_truncation",
    "estimate_secondary", "estimate_dist"),
  snapshots = NULL,
  secondary_type = c("confirmed", "total", "retracted", "unknown"),
  accumulate = "auto",
  complete = "auto",
  verbose = TRUE,
  quiet = FALSE
)

tbl_now_from_EpiNow2(data, ..., report_dates = NULL, verbose = TRUE)

Arguments

x: A tbl_now object.
...: Forwarded to as_tbl_now() (from); unused (to).
target: Which EpiNow2 entry point the result is for. See above.
snapshots: For "estimate_truncation": how many snapshots to emit, taken from the latest report dates. NULL (default) uses 5, matching EpiNow2::example_truncated. One snapshot per distinct report date is usually far more than the model can fit.
secondary_type: For "estimate_secondary": which revision outcomes to count in the secondary stream. One of "confirmed" (default), "total", "retracted" or "unknown". Pending cases are not on the revision axis, and "net" can be negative, which EpiNow2::estimate_secondary() cannot represent as a count stream.
accumulate: How to handle non-daily data. "auto" (default) lays a weekly series on EpiNow2's daily grid with an accumulate column; FALSE passes the rows through unchanged, which is almost always wrong (see Non-daily data). Ignored for "estimate_dist", which works in censoring windows rather than on a grid.
complete: For the series targets: fill event periods that have no reports at all with zeroes, out to the object's get_now(), via complete_zeroes(). "auto" (the default) does this for line-list input only. A line list has no row for a period in which nothing was reported, so a series built from one stops at the last period that has a report – short of the now, which is the period the nowcast is about. Count data is left exactly as supplied, because it can say "observed zero" itself. TRUE / FALSE force either behaviour; TRUE on count-cumulative input de-accumulates it first. Ignored for "estimate_dist", which works in censoring windows rather than on a grid.
verbose: Logical. Print the choices that were made.
quiet: Logical. A different channel from verbose: verbose controls the informational summary of what the conversion did, while quiet suppresses the lossy-conversion warning. Set both to keep a conversion entirely silent.
data: A tbl_now_epinow2_snapshots, or a plain list of date/confirm data frames (e.g. EpiNow2::example_truncated), in which case report_dates is required.
report_dates: For from: a Date vector, one per snapshot, saying when each was taken. Read from the object's attribute when it has one.

Value

For to, a data.frame or a tbl_now_epinow2_snapshots, according to target. For from, a tbl_now of data_type = "count-incidence".

Non-daily data

EpiNow2 models a daily process. As of 1.9.0 there is no timestep, interval or period argument on any of its entry points, so a weekly series passed as one row per week is read as one row per day and the fit is silently wrong on the time axis – no error, just an epidemic seven times too fast.

Its own answer is the accumulate column (see EpiNow2::fill_missing()): the series is laid on a daily grid and the filler days are marked to be added to the next real observation. accumulate = "auto" does this from get_event_units() for case-count targets, and from the shared report_units / revision_units grid for estimate_secondary. Units coarser than a week, and the "numeric" grid, are refused outright rather than approximated.

What EpiNow2 will not take

EpiNow2::estimate_delay() takes a bare vector of delays. Its own help now points at estimate_dist() as "the recommended replacement", and it throws away the censoring a tbl_now carries, so there is no target for it either. If you want it anyway, it is x$.delay.

Examples

data(denguedat)
nowobj <- tbl_now(denguedat[1:2000, ],
  event_date = "onset_week", report_date = "report_week", verbose = FALSE
)
## A single daily series for estimate_infections() -- the weekly data is laid
# on EpiNow2's daily grid.
head(tbl_now_to_EpiNow2(nowobj, verbose = FALSE, quiet = TRUE))
#>         date confirm accumulate
#> 1 1989-12-26      NA       TRUE
#> 2 1989-12-27      NA       TRUE
#> 3 1989-12-28      NA       TRUE
#> 4 1989-12-29      NA       TRUE
#> 5 1989-12-30      NA       TRUE
#> 6 1989-12-31      NA       TRUE

## Snapshots for estimate_truncation(), which uses the report dimension.
snaps <- tbl_now_to_EpiNow2(nowobj,
  target = "estimate_truncation", verbose = FALSE, quiet = TRUE
)
snaps
#> ── 5 reporting snapshots from a <tbl_now> ──────────────────────────────────────
#> • One per report date: "1991-02-04", "1991-02-11", "1991-02-18", "1991-02-25", and "1991-03-04"
#> • Rows each: 406, 413, 420, 427, and 434
#> • Now: "1991-03-04"
#> ℹ Pass this to `EpiNow2::estimate_truncation()`. `EpiNow2::estimate_secondary()` wants a single data frame of linked series instead -- not this.